Interactive Data Visualization

Row

Attrition Count

Attrition

Number of Employee Data Reviewed

1470

Monthly Income

Yes on Attrition

237

No on Attrition

1233

About Report

Project By:Heindel Adu, Stephen Johnson, Ross Fu, Anthony Yeung

Confidential: HIGHLY!

---
title: "Attrition Predictor Analysis"

output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: fill
    social: [ "twitter", "facebook", "menu"]
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(knitr)
library(DT)
library(rpivotTable)
library(ggplot2)
library(plotly)
library(dplyr)
library(openintro)
library(highcharter)
library(ggvis)
```


```{r}
data <- read.csv("~/Documents/Projects/SMU/rProjects/CaseStudy_02/CaseStudy_02/NumData.csv")
#str(data)
```

```{r}
mycolors <- c("blue", "#FFC125", "darkgreen", "darkorange", "darkblue")
```

Interactive Data Visualization
=====================================
Row
-------------------------------------
### Attrition Count

```{r}
valueBox(paste("Attrition"),
         color = "darkblue")
#unique.(data$Attrition)

#data %>%
#  summarise(Attrition = n())
```

### Number of Employee Data Reviewed

```{r}

valueBox(length(data$Attrition),
         icon = "fa-users")
```

### **Monthly Income**
```{r}
gauge(round(min(data$MonthlyIncome),
            digits = 2),
            min = 0,
            max = 25000,
      label = "Min Monthly Income",
            gaugeSectors(success = c(15000, 25000),
                         warning = c(5000,15000),
                         danger = c(0, 5000),
                         colors = c("green", "yellow", "red")))
```

```{r}
gauge(round(mean(data$MonthlyIncome),
            digits = 2),
            min = 0,
            max = 25000,
       label = "Avg Monthly Income",
            gaugeSectors(success = c(15000, 25000),
                         warning = c(5000,15000),
                         danger = c(0, 5000),
                         colors = c("green", "yellow", "red")))

```

```{r}
gauge(round(max(data$MonthlyIncome),
            digits = 2),
            min = 0,
            max = 25000,
       label = "Max Monthly Income",
            gaugeSectors(success = c(15000, 25000),
                         warning = c(5000,15000),
                         danger = c(0, 5000),
                         colors = c("green", "yellow", "red")))
```

### Yes on Attrition

```{r, Yes}
valueBox(sum(data$Attrition == "Yes"),
         icon = 'fa-user-o')

```


### No on Attrition

```{r, No}
valueBox(sum(data$Attrition == "No"),
         icon = 'fa-user')
```



About Report
========================================

##Project By:Heindel Adu, Stephen Johnson, Ross Fu, Anthony Yeung
Confidential: HIGHLY!